Find the right big data solution for your business or
organization
Big data management is one of the major challenges facing
business, industry, and not-for-profit organizations. Data sets
such as customer transactions for a mega-retailer, weather patterns
monitored by meteorologists, or social network activity can quickly
outpace the capacity of traditional data management tools. If you
need to develop or manage big data solutions, you'll appreciate how
these four experts define, explain, and guide you through this new
and often confusing concept. You'll learn what it is, why it
matters, and how to choose and implement solutions that work.
* Effectively managing big data is an issue of growing importance
to businesses, not-for-profit organizations, government, and IT
professionals
* Authors are experts in information management, big data, and a
variety of solutions
* Explains big data in detail and discusses how to select and
implement a solution, security concerns to consider, data storage
and presentation issues, analytics, and much more
* Provides essential information in a no-nonsense,
easy-to-understand style that is empowering
Big Data For Dummies cuts through the confusion and helps
you take charge of big data solutions for your organization.
Autorentext
Judith Hurwitz is an expert in cloud computing, information management, and business strategy.
Alan Nugent has extensive experience in cloud-based big data solutions.
Dr. Fern Halper specializes in big data and analytics.
Marcia Kaufman specializes in cloud infrastructure, information management, and analytics.
Zusammenfassung
Find the right big data solution for your business or organization
Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work.
- Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals
- Authors are experts in information management, big data, and a variety of solutions
- Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more
- Provides essential information in a no-nonsense, easy-to-understand style that is empowering
Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.
Inhalt
Introduction 1
About This Book 2
Foolish Assumptions 2
How This Book Is Organized 3
Part I: Getting Started with Big Data 3
Part II: Technology Foundations for Big Data 3
Part III: Big Data Management 3
Part IV: Analytics and Big Data 4
Part V: Big Data Implementation 4
Part VI: Big Data Solutions in the Real World 4
Part VII: The Part of Tens 4
Glossary 4
Icons Used in This Book 5
Where to Go from Here 5
Part I: Getting Started with Big Data 7
Chapter 1: Grasping the Fundamentals of Big Data 9
The Evolution of Data Management 10
Understanding the Waves of Managing Data 11
Wave 1: Creating manageable data structures 11
Wave 2: Web and content management 13
Wave 3: Managing big data 14
Defining Big Data 15
Building a Successful Big Data Management Architecture 16
Beginning with capture, organize, integrate, analyze, and act 16
Setting the architectural foundation 17
Performance matters 20
Traditional and advanced analytics 22
The Big Data Journey 23
Chapter 2: Examining Big Data Types 25
Defining Structured Data 26
Exploring sources of big structured data 26
Understanding the role of relational databases in big data 27
Defining Unstructured Data 29
Exploring sources of unstructured data 29
Understanding the role of a CMS in big data management 31
Looking at Real-Time and Non-Real-Time Requirements 32
Putting Big Data Together 33
Managing different data types 33
Integrating data types into a big data environment 34
Chapter 3: Old Meets New: Distributed Computing 37
A Brief History of Distributed Computing 37
Giving thanks to DARPA 38
The value of a consistent model 39
Understanding the Basics of Distributed Computing 40
Why we need distributed computing for big data 40
The changing economics of computing 40
The problem with latency 41
Demand meets solutions 41
Getting Performance Right 42
Part II: Technology Foundations for Big Data 45
Chapter 4: Digging into Big Data Technology Components 47
Exploring the Big Data Stack 48
Layer 0: Redundant Physical Infrastructure 49
Physical redundant networks 51
Managing hardware: Storage and servers 51
Infrastructure operations 51
Layer 1: Security Infrastructure 52
Interfaces and Feeds to and from Applications and the Internet 53
Layer 2: Operational Databases 54
Layer 3: Organizing Data Services and Tools 56
Layer 4: Analytical Data Warehouses 56
Big Data Analytics 58
Big Data Applications 58
Chapter 5: Virtualization and How It Supports Distributed Computing 61
Understanding the Basics of Virtualization 61
The importance of virtualization to big data 63
Server virtualization 64
Application virtualization 65
Network virtualization 66
Processor and memory virtualization 66
Data and storage virtualization 67
Managing Virtualization with the Hypervisor 68
Abstraction and Virtualization 69
Implementing Virtualization to Work with Big Data 69
Chapter 6: Examining the Cloud and Big Data 71
Defining the Cloud in the Context of Big Data 71
Understanding Cloud Deployment and Delivery Models 72
Cloud deployment models 73
Cloud delivery models 74
The Cloud as an Imperative for Big Data 75
Making Use of the Cloud for Big Data 77
Providers in the Big Data Cloud Market 78
Amazon's Public Elastic Compute Cloud 78
Google big data services 79
Microsoft Azure 8...